mcp-mssql-secure

Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Each tool serves a distinct purpose: query for ad-hoc read-only SQL, list_tables and list_schemas for enumeration, describe_table for table structure, and programmable-object tools for stored procedures/functions/views/triggers. No overlapping boundaries that would confuse an agent.
Naming Consistency5/5
Tool names follow a clear verb_noun pattern: list_* for enumeration, describe_* for metadata, and query/connect_db as simple verbs. Consistent snake_case throughout.
Tool Count5/5
Seven tools is a well-scoped size for a read-only database exploration server, covering querying, listing, and describing without unnecessary bloat or missing essentials.
Completeness5/5
The surface fully covers read-only database exploration: execute queries, discover tables/schemas/programmable objects, and inspect their definitions. No obvious dead ends for typical inspection workflows.
Average 3.3/5 across 7 of 7 tools scored. Lowest: 1.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full behavioral transparency. It only mentions a lock condition and does not disclose what the tool does, what happens upon connection, or any side effects. This is a severe gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, but it is under-specified rather than concise. It omits essential purpose and usage information, so the brevity is not effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters, no output schema, and no annotations, the description should explain behavioral context and parameters. It only provides a disabled condition, leaving the agent without enough information to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all 7 parameters have descriptions in the schema. The tool description adds no parameter information, but the schema already provides the baseline meaning, earning a 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description does not state what the tool does. It only says 'Disabled when MSSQL_LOCK_CONNECTION=true' which is a conditional state, not a purpose. No verb or resource is mentioned, so the agent cannot infer that this tool connects to a database.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool or how it relates to sibling tools like query or list_tables. The only hint is to use environment variables when disabled, but that is a configuration fallback, not a usage guideline for the tool itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. 'Get table structure' implies a read-only operation but does not specify what 'structure' includes (columns, types, constraints, indexes), nor any potential error behavior or access requirements. This is a significant gap for a schema-inspection tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It is efficient for the purpose, though it could include more behavioral detail without being overly verbose. The brevity is acceptable but not exceptional.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations and output schema, the description is too incomplete. It fails to explain what 'structure' entails or how the result relates to sibling tools. For a tool that likely returns detailed schema information, this minimal description leaves the agent under-informed about expected output and capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage for both parameters (table and schema), including a default for schema. The description adds no extra meaning beyond the schema, so the baseline of 3 is appropriate. It does not explain parameter formatting or relationships beyond what the schema already states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get table structure' uses a specific verb and resource, clearly indicating the tool retrieves schema information for a table. It distinguishes reasonably from siblings like 'query' (data) and 'list_tables' (names only), though it doesn't explicitly contrast with 'describe_programmable_object'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. It does not mention prerequisites (e.g., connect_db first), nor does it contrast with list_tables or describe_programmable_object. Users must infer usage from the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the basic function but does not reveal important details like schema filtering behavior, whether system tables are included, or the output format. This is a significant gap for a tool that could interact with various database states.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that directly states the purpose without wasted words. It is front-loaded and efficiently communicates the tool's core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite being a simple tool, the description lacks completeness given the absence of an output schema and annotations. It does not explain what is returned (e.g., table names only, metadata), how the schema parameter affects results, or any behavior beyond the bare listing. This is insufficient for an agent to predict the tool's direct response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single optional parameter 'schema' is already fully documented in the input schema (100% coverage), including its default value 'dbo'. The description adds no additional meaning beyond the schema, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List tables in the database.' This is a specific verb+resource combination that distinguishes it from siblings like list_schemas or describe_table, though it does not explicitly differentiate edge cases (e.g., list_programmable_objects).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives. It does not mention exclusion criteria, prerequisites, or relationships to sibling tools such as describe_table or query, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the read-only and metadata nature, which gives a basic safety signal. However, it does not mention potential result set size, whether it returns names only or full definitions, or any behavior regarding missing schemas or filters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of eight words, front-loaded with the key verb and object. Every word earns its place, and there is no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two optional parameters and no output schema. The description covers the core purpose but does not describe return value shape or any behavioral constraints beyond 'metadata'. For a listing tool, this is adequate but leaves room for more detail about what the result actually contains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already explains both parameters (schema with default dbo, object_type with allowed values). The description adds no extra meaning about parameters, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists stored procedures, functions, views, and triggers, with an explicit read-only metadata qualifier. It distinguishes itself from sibling tools like list_tables (which lists tables) and describe_programmable_object (which targets a single object).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied by the description—agents can infer it is for enumerating programmable objects—but there is no explicit guidance about when to use this tool versus alternatives, nor any exclusionary conditions. No mention of list_tables or describe_programmable_object as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The verb 'List' indicates a read-only operation, but the description does not disclose permissions, return format, or any potential side effects. It is minimally adequate but lacks extra behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no filler. Every word earns its place, and it is front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description is largely complete. It clearly states the tool lists all schemas in the database, which is sufficient for an agent to understand the tool's scope, though it does not mention details like whether system schemas are included.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the schema already fully covers parameter semantics. The baseline of 4 applies, and the description adds no unnecessary parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('all schemas in the database'), making the tool's purpose clear. It also implicitly distinguishes from siblings like list_tables (tables vs schemas) and describe_programmable_object.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives such as list_tables or describe_table. It only states what the tool does, leaving the agent to infer usage context without explicit comparisons or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the read-only nature and allowed SQL commands, which is valuable safety information. However, it does not mention return format, error behavior, or permission requirements, preventing a higher score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the verb 'Execute', and every word adds value. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with full schema coverage and no output schema, the description covers the essential behavioral constraints (read-only, allowed statements) but omits any mention of the result shape or pagination. This is a minor gap given the tool's low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes the sql parameter as a read-only query with placeholder syntax. The description adds no new parameter semantics beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool executes a read-only SQL query and enumerates supported statement types (SELECT, WITH, EXPLAIN, TABLE, VALUES), making its purpose specific and distinct from siblings that list/describe database metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for running SQL queries but does not explicitly state when to prefer it over sibling tools or exclude non-read-only statements. It lacks explicit comparative guidance, though the read-only constraint gives some direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of exposing behavior. It explicitly discloses that the operation is read-only and does not execute, which are critical safety-related behavioral traits. It does not mention error behavior or required permissions, but the core non-destructive nature is clearly stated, and the claim that it returns 'full definition and parameters' conveys the primary output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and resource, then adds the read-only caveat. Every phrase earns its place—no redundant words, and it avoids restating the tool name or schema details. Excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description must convey what the tool returns, and 'full T-SQL definition and parameters' does that adequately. It also includes the object types and the read-only behavior. The only minor gap is not specifying the return format (e.g., plain text vs. structured JSON), but given the simple parameter set and clear focus, the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for all three parameters, including defaults and optional behavior (auto-detection for object_type). The description text adds the list of supported object types but does not elaborate on parameter syntax or relationships beyond the schema. Since schema coverage is 100%, the baseline of 3 is appropriate; the description adds minimal extra semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Get full T-SQL definition and parameters') and the target resource ('stored procedure, function, view, or trigger'). This distinguishes it from sibling tools like list_programmable_objects (which lists objects) and describe_table (which describes table structure), making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly distinguishes when to use this tool by noting it is read-only and does not execute, which sets it apart from query. It also lists the applicable object types, giving clear context. However, it does not explicitly name alternatives or state 'use this when you need the definition, not to run it,' so the guidance is clear but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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